Triple
T975555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | When the Saints Go Marching In |
E21043
|
entity |
| Predicate | isFrequentlyAdapted |
P22743
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: true | Statement: [When the Saints Go Marching In, isFrequentlyAdapted, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrequentlyAdapted Context triple: [When the Saints Go Marching In, isFrequentlyAdapted, true]
-
A.
adaptationStatus
Indicates the current state or progress of how something has been adapted or adjusted in response to specific conditions, requirements, or contexts.
-
B.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
C.
adaptedTo
Indicates that one entity has been modified, adjusted, or evolved to function effectively within the conditions, requirements, or characteristics defined by another entity.
-
D.
adaptation
Indicates a relationship where one entity changes or is modified to better suit, function within, or correspond to another entity or context.
-
E.
adaptedAs
Indicates that one work, concept, or entity has been transformed or re-created into another form or medium based on the original.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b46234c88190b2bfc9cafe59d7f7 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a6aa2c8190aebba71320ab678f |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b38630848190bd3898a4f42018ad |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.